Open source software has had an expanding role in the development of image analysis routines for radiology research applications. Compared to commercial proprietary software, open source software is often more adaptable and economical. The purpose of this workshop is to familiarize participants with the features of ImageJ/FIJI , an open source image processing program The utility of ImageJ for performing automated image filtration, segmentation and registration tasks that are repeatable and can be tailored using information on the DICOM headers of images will be discussed. Case studies using clinical images will be used to demonstrate the capabilities of ImageJ. These demonstrations will also show how the capabilities of this software can be expanded using macros scripts and plug-ins (FIJI only). A quick demonstration of WEKA (https://www.cs.waikato.ac.nz/ml/weka/ ) a machine learning package embedded in FIJI.